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Full-Text Articles in Life Sciences
Spectral Gene Set Enrichment (Sgse), H Robert Frost, Zhigang Li, Jason H. Moore
Spectral Gene Set Enrichment (Sgse), H Robert Frost, Zhigang Li, Jason H. Moore
Dartmouth Scholarship
Gene set testing is typically performed in a supervised context to quantify the association between groups of genes and a clinical phenotype. In many cases, however, a gene set-based interpretation of genomic data is desired in the absence of a phenotype variable. Although methods exist for unsupervised gene set testing, they predominantly compute enrichment relative to clusters of the genomic variables with performance strongly dependent on the clustering algorithm and number of clusters. We propose a novel method, spectral gene set enrichment (SGSE), for unsupervised competitive testing of the association between gene sets and empirical data sources. SGSE first computes …
How To Get The Most From Microarray Data: Advice From Reverse Genomics, Ivan P. Gorlov, Ji-Yeon Yang, Jinyoung Byun, Christopher Logothetis, Olga Y. Gorlova, Kim-Anh Do, Christopher Amos
How To Get The Most From Microarray Data: Advice From Reverse Genomics, Ivan P. Gorlov, Ji-Yeon Yang, Jinyoung Byun, Christopher Logothetis, Olga Y. Gorlova, Kim-Anh Do, Christopher Amos
Dartmouth Scholarship
Whole-genome profiling of gene expression is a powerful tool for identifying cancer-associated genes. Genes differentially expressed between normal and tumorous tissues are usually considered to be cancer associated. We recently demonstrated that the analysis of interindividual variation in gene expression can be useful for identifying cancer associated genes. The goal of this study was to identify the best microarray data–derived predictor of known cancer associated genes. We found that the traditional approach of identifying cancer genes—identifying differentially expressed genes—is not very efficient. The analysis of interindividual variation of gene expression in tumor samples identifies cancer-associated genes more effectively. The results …
Microbial Nad Metabolism: Lessons From Comparative Genomics, Francesca Gazzaniga, Rebecca Stebbins, Sheila Z. Chang, Mark A. Mcpeek, Charles Brenner
Microbial Nad Metabolism: Lessons From Comparative Genomics, Francesca Gazzaniga, Rebecca Stebbins, Sheila Z. Chang, Mark A. Mcpeek, Charles Brenner
Dartmouth Scholarship
NAD is a coenzyme for redox reactions and a substrate of NAD-consuming enzymes, including ADP-ribose transferases, Sir2-related protein lysine deacetylases, and bacterial DNA ligases. Microorganisms that synthesize NAD from as few as one to as many as five of the six identified biosynthetic precursors have been identified. De novo NAD synthesis from aspartate or tryptophan is neither universal nor strictly aerobic. Salvage NAD synthesis from nicotinamide, nicotinic acid, nicotinamide riboside, and nicotinic acid riboside occurs via modules of different genes. Nicotinamide salvage genes nadV and pncA, found in distinct bacteria, appear to have spread throughout the tree of life …
Genomic And Proteomic Profiling Of Responses To Toxic Metals In Human Lung Cells, Angeline S. Andrew, Amy J. Warren, Aaron Barchowsky, Kaili A. Temple, Linda Klei, Nicole V. Soucy, Kimberly A. O'Hara, Joshua W. Hamilton
Genomic And Proteomic Profiling Of Responses To Toxic Metals In Human Lung Cells, Angeline S. Andrew, Amy J. Warren, Aaron Barchowsky, Kaili A. Temple, Linda Klei, Nicole V. Soucy, Kimberly A. O'Hara, Joshua W. Hamilton
Dartmouth Scholarship
Examining global effects of toxic metals on gene expression can be useful for elucidating patterns of biological response, discovering underlying mechanisms of toxicity, and identifying candidate metal-specific genetic markers of exposure and response. Using a 1,200 gene nylon array, we examined changes in gene expression following low-dose, acute exposures of cadmium, chromium, arsenic, nickel, or mitomycin C (MMC) in BEAS-2B human bronchial epithelial cells. Total RNA was isolated from cells exposed to 3 M Cd(II) (as cadmium chloride), 10 M Cr(VI) (as sodium dichromate), 3 g/cm2 Ni(II) (as nickel subsulfide), 5 M or 50 M As(III) (as sodium arsenite), or …